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Yehuda Dar
Yehuda Dar
Postdoctoral Researcher, ECE Department, Rice University
Verified email at rice.edu - Homepage
Title
Cited by
Cited by
Year
Postprocessing of compressed images via sequential denoising
Y Dar, AM Bruckstein, M Elad, R Giryes
IEEE Transactions on Image Processing 25 (7), 3044-3058, 2016
652016
Motion-compensated coding and frame rate up-conversion: Models and analysis
Y Dar, AM Bruckstein
IEEE Transactions on Image Processing 24 (7), 2051-2066, 2015
412015
A farewell to the bias-variance tradeoff? an overview of the theory of overparameterized machine learning
Y Dar, V Muthukumar, RG Baraniuk
arXiv preprint arXiv:2109.02355, 2021
202021
Improving low bit-rate video coding using spatio-temporal down-scaling
Y Dar, AM Bruckstein
arXiv preprint arXiv:1404.4026, 2014
112014
Optimized pre-compensating compression
Y Dar, M Elad, AM Bruckstein
IEEE Transactions on Image Processing 27 (10), 4798-4809, 2018
102018
Double double descent: on generalization errors in transfer learning between linear regression tasks
Y Dar, RG Baraniuk
arXiv preprint arXiv:2006.07002, 2020
92020
Restoration by compression
Y Dar, M Elad, AM Bruckstein
IEEE Transactions on Signal Processing 66 (22), 5833-5847, 2018
92018
Subspace fitting meets regression: The effects of supervision and orthonormality constraints on double descent of generalization errors
Y Dar, P Mayer, L Luzi, R Baraniuk
International Conference on Machine Learning, 2366-2375, 2020
62020
Algorithms for piecewise constant signal approximations
L Bergerhoff, J Weickert, Y Dar
2019 27th European Signal Processing Conference (EUSIPCO), 1-5, 2019
52019
System-aware compression
Y Dar, M Elad, AM Bruckstein
2018 IEEE International Symposium on Information Theory (ISIT), 2226-2230, 2018
52018
The Common Intuition to Transfer Learning Can Win or Lose: Case Studies for Linear Regression
Y Dar, D LeJeune, RG Baraniuk
arXiv preprint arXiv:2103.05621, 2021
4*2021
Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective
G Somepalli, L Fowl, A Bansal, P Yeh-Chiang, Y Dar, R Baraniuk, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
32022
Benefiting from duplicates of compressed data: Shift-based holographic compression of images
Y Dar, AM Bruckstein
Journal of Mathematical Imaging and Vision 63 (3), 380-393, 2021
32021
On high-resolution adaptive sampling of deterministic signals
Y Dar, AM Bruckstein
Journal of Mathematical Imaging and Vision 61 (7), 944-966, 2019
32019
Compression for multiple reconstructions
Y Dar, M Elad, AM Bruckstein
2018 25th IEEE International Conference on Image Processing (ICIP), 440-444, 2018
32018
Image restoration via successive compression
Y Dar, AM Bruckstein, M Elad
2016 Picture Coding Symposium (PCS), 1-5, 2016
32016
Reducing artifacts of intra-frame video coding via sequential denoising
Y Dar, AM Bruckstein, M Elad, R Giryes
2016 IEEE International Conference on the Science of Electrical Engineering …, 2016
22016
Double descent and other interpolation phenomena in GANs
L Luzi, Y Dar, R Baraniuk
arXiv preprint arXiv:2106.04003, 2021
12021
Modular ADMM-Based Strategies for Optimized Compression, Restoration, and Distributed Representations of Visual Data
Y Dar, AM Bruckstein
Handbook of Mathematical Models and Algorithms in Computer Vision and …, 2021
2021
Regularized Compression of MRI Data: Modular Optimization of Joint Reconstruction and Coding
V Corona, Y Dar, G Williams, CB Schönlieb
arXiv preprint arXiv:2010.04065, 2020
2020
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